Flammability Characteristics of Light Hydrocarbons and Their Mixtures at Elevated Conditions

Accurate data of flammability limits for flammable gases and vapors are needed to prevent fires and explosions. The flammability limit is the maximum or minimum fuel concentration at which a gas mixture is flammable in a given atmosphere. Even though investigations of flammability limit have been carried out for decades, data are still scarce and sometimes unavailable. Through years of study, people have developed estimation and approximation methods for the prediction of flammability limit. However, these methods exhibit significant variations, especially at elevated temperatures and pressures. This research focuses on the flammability limits of light hydrocarbons (methane, propane, and ethylene) and their binary mixtures at normal and elevated conditions. The flammability limits of pure light hydrocarbons, and binary mixtures were determined experimentally at the temperature up to 300ºC and initial pressure up to 2atm. The experiments were conducted in a closed cylindrical stainless steel vessel with upward flame propagation. The combustion behavior and different flammability criteria were compared and the 7% pressure increment was determined as the most appropriate criterion for the test. Experimentally measured pure hydrocarbon flammability limits are compared with existing data in the literature to study the influence of temperature, pressure, and apparatus set. An estimation model was developed for the prediction of pure light hydrocarbon flammability limit at elevated conditions. For binary mixtures, experiment data were compared with predictions from Le Chatelier’s Rule to validate its application at elevated conditions. It was discovered that Le Chatelier’s rule works fairly well for the lower flammability limit of mixtures only. The explanation of the difference between upper flammability limit predictions with experimental data was investigated through the reaction pathway analysis using ANSYS CHEMKIN software. It was proved that for the upper flammability limit test, ethylene was more reactive than methane and propane in the combustion process. Finally, a modified Le Chatelier’s rule model was developed and validated using experimental data

Numerical Simulation of Hot Accretion Flows (III): Revisiting wind properties using trajectory approach

Previous MHD simulations have shown that wind must exist in black hole hot accretion flows. In this paper, we continue our study by investigating the detailed properties of wind, such as mass flux and poloidal speed, and the mechanism of wind production. For this aim, we make use of a three dimensional GRMHD simulation of hot accretion flows around a Schwarzschild black hole. The simulation is designed so that the magnetic flux is not accumulated significantly around the black hole. To distinguish real wind from turbulent outflows, we track the trajectories of the virtual Largrangian particles from simulation data. We find two types of real outflows, i.e., a quasi-relativistic jet close to the axis and a sub-relativistic wind subtending a much larger solid angle. Most of the wind originates from the surface layer of the accretion flow. The poloidal wind speed almost remains constant once they are produced, but the flux-weighted wind speed roughly follows $v_{\rm p, wind}(r)\approx 0.25 v_k(r)$. The mass flux of jet is much lower but the speed is much higher, $v_{\rm p,jet}\sim (0.3-0.4) c$. Consequently, both the energy and momentum fluxes of the wind are much larger than those of the jet. We find that the wind is produced and accelerated primarily by the combination of centrifugal force and magnetic pressure gradient, while the jet is mainly accelerated by magnetic pressure gradient. Finally, we find that the wind production efficiency $\epsilon_{\rm wind}\equiv\dot{E}_{\rm wind}/\dot{M}_{\rm BH}c^2\sim 1/1000$, in good agreement with the value required from large-scale galaxy simulations with AGN feedback.Comment: 13 pages, 13 figures; submitted to Ap

Transparency, price informativeness, and stock return synchronicity: Theory and evidence

This paper argues that contrary to the conventional wisdom, stock return synchronicity (or R(2)) can Increase when transparency improves In a simple model, we show that in more transparent environments stock prices should be more informative about future events Consequently when the events actually happen in the future there should be less surprise" (i e less new information is impounded into the stock price) Thus a more informative stock price today means higher return synchronicity in the future We find empirical support for our theoretical predictions in 3 settings namely firm age seasoned equity offerings (SEOs), and listing of American Depositary Receipts (ADRs

Fe3O4/Au magnetic nanoparticle amplification strategies for ultrasensitive electrochemical immunoassay of alfa-fetoprotein

Ning Gan1*, Haijuan Jin1*, Tianhua Li1, Lei Zheng21The State Key Laboratory Base of Novel Functional Materials and Preparation Science, Faculty of Material Science and Chemical Engineering, Ningbo University, Ningbo, 2Department of Laboratory Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, People's Republic of China *Both authors contributed equally to this workBackground: The purpose of this study was to devise a novel electrochemical immunosensor for ultrasensitive detection of alfa-fetoprotein based on Fe3O4/Au nanoparticles as a carrier using a multienzyme amplification strategy.Methods and results: Greatly enhanced sensitivity was achieved using bioconjugates containing horseradish peroxidase (HRP) and a secondary antibody (Ab2) linked to Fe3O4/Au nanoparticles (Fe3O4/Au-HRP-Ab2) at a high HRP/Ab2 ratio. After a sandwich immunoreaction, the Fe3O4/Au-HRP-Ab2 captured on the electrode surface produced an amplified electrocatalytic response by reduction of enzymatically oxidized hydroquinone in the presence of hydrogen peroxide. The high content of HRP in the Fe3O4/Au-HRP-Ab2 could greatly amplify the electrochemical signal. Under optimal conditions, the reduction current increased with increasing alfa-fetoprotein concentration in the sample, and exhibited a dynamic range of 0.005–10 ng/mL with a detection limit of 3 pg/mL.Conclusion: The amplified immunoassay developed in this work shows good precision, acceptable stability, and reproducibility, and can be used for detection of alfa-fetoprotein in real samples, so provides a potential alternative tool for detection of protein in the laboratory. Furthermore, this immunosensor could be regenerated by simply using an external magnetic field.Keywords: Fe3O4/Au nanoparticles, alfa-fetoprotein, sandwich immunoassay, electrochemical immunosenso

Bulge formation from SSCs in a responding cuspy dark matter halo

We simulate the bulge formation in very late-type dwarf galaxies from circumnuclear super star clusters (SSCs) moving in a responding cuspy dark matter halo (DMH). The simulations show that (1) the response of DMH to sinking of SSCs is detectable only in the region interior to about 200 pc. The mean logarithmic slope of the responding DM density profile over that area displays two different phases: the very early descent followed by ascent till approaching to 1.2 at the age of 2 Gyrs. (2) the detectable feedbacks of the DMH response on the bulge formation turned out to be very small, in the sense that the formed bulges and their paired nuclear cusps in the fixed and the responding DMH are basically the same, both are consistent with $HST$ observations. (3) the yielded mass correlation of bulges to their nuclear (stellar) cusps and the time evolution of cusps' mass are accordance with recent findings on relevant relations. In combination with the consistent effective radii of nuclear cusps with observed quantities of nuclear clusters, we believe that the bulge formation scenario that we proposed could be a very promising mechanism to form nuclear clusters.Comment: 27 pages, 11 figures, accepted for publication in Ap

Large Language Models for Robotics: A Survey

The human ability to learn, generalize, and control complex manipulation tasks through multi-modality feedback suggests a unique capability, which we refer to as dexterity intelligence. Understanding and assessing this intelligence is a complex task. Amidst the swift progress and extensive proliferation of large language models (LLMs), their applications in the field of robotics have garnered increasing attention. LLMs possess the ability to process and generate natural language, facilitating efficient interaction and collaboration with robots. Researchers and engineers in the field of robotics have recognized the immense potential of LLMs in enhancing robot intelligence, human-robot interaction, and autonomy. Therefore, this comprehensive review aims to summarize the applications of LLMs in robotics, delving into their impact and contributions to key areas such as robot control, perception, decision-making, and path planning. We first provide an overview of the background and development of LLMs for robotics, followed by a description of the benefits of LLMs for robotics and recent advancements in robotics models based on LLMs. We then delve into the various techniques used in the model, including those employed in perception, decision-making, control, and interaction. Finally, we explore the applications of LLMs in robotics and some potential challenges they may face in the near future. Embodied intelligence is the future of intelligent science, and LLMs-based robotics is one of the promising but challenging paths to achieve this.Comment: Preprint. 4 figures, 3 table